Browsing by Author "Etterson, Julie R."
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Item Aster Models with Random Effects via Penalized Likelihood(2012-10-09) Geyer, Charles J.; Ridley, Caroline E.; Latta, Robert G.; Etterson, Julie R.; Shaw, Ruth G.This technical report works out details of approximate maximum likelihood estimation for aster models with random effects. Fixed and random effects are estimated by penalized log likelihood. Variance components are estimated by integrating out the random effects in the Laplace approximation of the complete data likelihood following Breslow and Clayton (1993), which can be done analytically, and maximizing the resulting approximate missing data likelihood. A further approximation treats the second derivative matrix of the cumulant function of the exponential family where it appears in the approximate missing data log likelihood as a constant (not a function of parameters). Then first and second derivatives of the approximate missing data log likelihood can be done analytically. Minus the second derivative matrix of the approximate missing data log likelihood is treated as approximate Fisher information and used to estimate standard errors.Item Aster Models with Random Effects via Penalized Likelihood(University of Minnesota, 2010-07) Geyer, Charles J.; Ridley, Caroline E.; Latta, Robert G.; Etterson, Julie R.; Shaw, Ruth G.Item Evolutionary responses to changing climate(2005) Davis, Margaret B.; Shaw, Ruth G.; Etterson, Julie R.Until now, Quaternary paleoecologists have regarded evolution as a slow process relative to climate change, predicting that the primary biotic response to changing climate is not adaptation, but instead (1) persistence in situ if changing climate remains within the species' tolerance limits, (2) range shifts (migration) to regions where climate is currently within the species' tolerance limits, or (3) extinction. We argue here that all three of these outcomes involve evolutionary processes. Genetic differentiation within species is ubiquitous, commonly via adaptation of populations to differing environmental conditions. Detectable adaptive divergence evolves on a time scale comparable to change in climate, within decades for herbaceous plant species, and within centuries or millennia for longer-lived trees, implying that biologically significant evolutionary response can accompany temporal change in climate. Models and empirical studies suggest that the speed with which a population adapts to a changing environment affects invasion rate of new habitat and thus migration rate, population growth rate and thus probability of extinction, and growth and mortality of individual plants and thus productivity of regional vegetation. Recent models and experiments investigate the stability of species tolerance limits, the influence of environmental gradients on marginal populations, and the interplay of demography, gene flow, mutation rate, and other genetic processes on the rate of adaptation to changed environments. New techniques enable ecologists to document adaptation to changing conditions directly by resurrecting ancient populations from propagules buried in decades-old sediment. Improved taxonomic resolution from morphological studies of macrofossils and DNA recovered from pollen grains and macroremains provides additional information on range shifts, changes in population sizes, and extinctions. Collaboration between paleoecologists and evolutionary biologists can refine interpretations of paleorecords, and improve predictions of biotic response to anticipated climate change.Item More Supporting Data Analysis for "Unifying Life History Analysis for Inference of Fitness and Population Growth"(University of Minnesota, 2007-11) Geyer, Charles J.; Wagenius, Stuart; Shaw, Ruth G.; Hangelbroek, Helen H.; Etterson, Julie R.Item Supporting Data Analysis for "Unifying Life History Analysis for Inference of Fitness and Population Growth"(University of Minnesota, 2007-07) Geyer, Charles J.; Wagenius, Stuart; Shaw, Ruth G.; Hangelbroek, Helen H.; Etterson, Julie R.Item Yet More Supporting Data Analysis for "Unifying Life History Analysis for Inference of Fitness and Population Growth"(University of Minnesota, 2008-01) Geyer, Charles J.; Wagenius, Stuart; Shaw, Ruth G.; Hangelbroek, Helen H.; Etterson, Julie R.